1. Field of the Invention
The invention relates generally to systems for identifying organic liquids, and more particularly to a field-utilizable analytical instrument using a semiconductor gas sensor array and neural network processor to identify and characterize liquid fuels.
There is an increasing demand for small, rugged and portable instruments to identify organic substances in the field. In particular, there is need for a field instrument capable of rapid, on-site analysis and identification of aviation and automotive fuels. Some of the applications for such an instrument are ensuring that an aircraft is refueled with the correct grade of fuel, checking gasoline at the point of sale for alcohol and/or octane number (ON), and verifying that fuel storage facilities contain the proper grades of fuel. All of these needs as well as other safety-related applications would be met by an instrument capable of quick determinations of fuel type and octane number in the field.
The usual test for octane number is the rigorous CFR test which is based on running the fuel through an internal combustion engine, and requires sophisticated equipment and hours of setup time. Laboratory-grade instruments normally used in conjunction with octane number measurements may involve infrared spectrum analysis, multivariate regression analysis, flame reactions, mass spectrometers, gas chromatographs, microprocessor-controlled octane analyzers, and others. The laboratory instruments often have the capability to analyze a large number of compounds at low concentrations, but generally are too cumbersome for field use and often require time-consuming sample preparation as well.
2. Description of the Prior Art
The first examples of prior art involve gas sensor arrays coupled with pattern recognition approaches to identify unknown gas samples. The first of these (P. K. Clifford, "Selective Gas Detection and Measurement System", U.S. Pat. No. 4,542,640, Issued Sep. 24, 1985), is a chemometric approach that relies on the solution of linear equations. Clifford's method is unsuitable when dealing with liquid fuels, which may have tens or hundreds of individual organic constituents. Clifford's approach also requires that the number of sensors be greater than or equal to the number of unknown gases. The second example (A. Ikegami and M. Kaneyasu, "Olfactory Detection Using Integrated Sensor", Proc. of Transducers '85, 1985 Intl. Conf. on Solid State Sensors and Actuators, Philadelphia, Pa., 136-139, 1985), uses a microcomputer to mathematically calculate the similarities in patterns of certain essentially pure substances that are not necessarily chemically similar.
Recent work by B. S. Hoffheins at the Oak Ridge National Laboratory showed that the problem of qualitative gas analysis of a few essentially pure substances can be greatly simplified through the use of semiconductor gas sensors together with pattern recognition and/or neural networks (B. S. Hoffheins, Master's Thesis, University of Tennessee, 1989). Hoffheins reported results of using a nine sensor array with a neural network to analyze the patterns of a six item group comprising isopropanol, methanol, ethanol, heptane, hexane, and hexane-2% ethanol. In addition, an integrated sensor array was used to obtain patterns of one gasoline sample and samples of the same gasoline with either methanol or ethanol added to it. Although slight differences were noted in the patterns, no attempt was made to classify the gasoline samples with a neural network.
In 1991, Gardner and Bartlett in separate papers reported results similar to Hoffheins (J. W. Gardner, "Detection of Vapours and Odours from a Multisensor Array Using Pattern Recognition Part I. Principal Component and Cluster Analysis", Sensors and Actuators B, Vol 4, 109-115, 1991), (P. N. Bartlett, "The Design of an Artificial Olfactory System, " Paper no. 253, Pittsburgh Conference, Chicago, March 1991).
Also in 1991, anonymous authors reported applying a neural network to the spectroscopic analysis of infrared data ("Determination of Fuel Properties", Research Disclosure, pp. 571-572, 1991). This last reference appears to be the first attempt to produce an instrument designed specifically for determination of octane number by indirect means, that is, without actually burning the fuel in an engine and observing knock characteristics.